When the robot has the knowledge of the human state and intent, it must respond promptly with appropriate actions to facilitate the collaborative task execution. This typically means generation of motion trajectories and often simultaneous impedance adaptation. The trajectories can be chosen to optimize task-related objectives: reducing trajectory jerk [1]}, [2]}, minimize positioning error [3]}, [4]}, [5]}, or render appropriate velocity response [6]}, [7]}. In addition, human operator-related objectives can be optimized as well, such as minimizing interaction forces [8]}, or metabolic cost [9]}. A common rule is that the robot can take over aspects of the task that require precision, while the human can handle adaption to variations. The `minimum intervention principle' [10]} follows this rule, where uncertain DOF should have a lower stiffness [11]}, [12]}, which can also be interpreted as a risk-sensitive control. Nevertheless, such an approach is not reasonable for all interactive tasks that involve physical constraints [13]}.
